In the past, cameras and radars have been used to detect troop movements and presence of vehicles, be they light weight vehicles or tanks and bulldozers.
In order to surveil a given area, these sensors are scattered about, with the sensor providing information as to its location and sensed value. However camera and radar sensors require large amounts of power, both for the sensing operation and for the transmitting operation.
These sensors are normally battery powered and these types of sensors may last less than a day. On the other hand if one is seeking to detect vehicles using a geophone, geophones are very long lifetime devices because the geophone does not consume power. It is noted that geophones operate with a moving coil within a magnet so that the geophone generates its own electricity when the surface to which it is attached vibrates or shakes. Thus, geophones are in essence self-powered.
However, power is an issue when processing the output of geophones to determine that a target of interest exists. The high power consumption is in part due to the very large number of signals coming out of the transducer and in the past there has been a high computational load associated with characterizing geophone signals.
However if geophones can be utilized, then in terms of longevity one has a large advantage in terms of battery life that sensors can be deployed and be in place for long periods of time.
It has been thought that geophones do not have output signal characteristics that are distinct enough to be able to characterize what is shaking the ground. Certainly the geophone output is nowhere near as distinct as a camera image where one could see a picture and therefore determine not only that what is detected is a vehicle, but what type of vehicle it is. Thus picking out what constitutes a vehicle is quite subtle when utilizing geophone signals.
As a result, geophones were not utilized to detect vehicles. Nor were they utilized to detect the size of a vehicle, or to characterize a vehicle, for instance as being a passenger vehicle or a military vehicle.
It will be appreciated that geophones fundamentally measure ground vibration, usually in a frequency range between 15 hertz to 100 hertz. Because they are very low frequency signals the signatures of different weight vehicles have not heretofore offered enough information for vehicle detection and identity.
The reason that geophones have not been particularly useful up until the present time in determining the identity of the seismic source is that there are a large number of different objects which shake the ground. Not only can the ground shaking be produced by vehicles, wind blowing through a stand of trees causes the ground to shake, thus producing a local seismic phenomenon unrelated to vehicle detection. Also, electrical generators for example generate seismic noise which complicates vehicle detection due to the panoply of seismic noise sources, both natural and manmade.
For instance, assuming that there is a power outage in the area, diesel generators may kick in causing significant ground vibration. Thus, historically there has not been much benefit seen for using geophones. If a method could be provided that uses geophones for detecting and classifying vehicles, then their low cost, self-power, and low observability become attractive, especially since one can simply bury them in the ground to provide for stealthy surveillance.
Aside from the very low power consumption of the geophones, it is also desirable in any system to provide processors which minimize battery drain. It is noted that divide-by operations consume a considerable amount of power due to the number of floating point operations involved. Thus, processing which simply implements a mathematical formula for processing sensor outputs often results in too large a computational load.